The present invention relates to the field of information sharing, and in particular to the field of web-based shared document repositories and document recommender systems.
Web-based shared documents repositories support cooperation of users by allowing them to efficiently share objects, generally documents, but also a calendar, a bulletin board or the like, to have threaded conversation, to set access rights, to organize the information into workspaces, or folders, but they can also contribute to user information overflow.
An example of a shared document repository includes DocuShare® developed by Xerox Corporation. DocuShare® is a web-based document management system that allows users to store, access, and share information in a collaborative work environment with access control. In addition, DocuShare® allows any user on any system to post and retrieve information in any format such as text, scanned images, video and sound files using an Internet browser. Such shared document repositories allow information to be shared in a manner that is as simple as having the information available on the user's own local hard disk, whereas in reality the information is centrally stored.
More specifically, DocuShare® provides in a repository a list of folders and document objects available, together with metadata such as date and size. Document objects that are added to the repository are indexed to allow rapid retrieval using a search engine and entering key words. Access to the repository is controlled by defining user permissions to the repository itself or to a document or sets of documents in the repository. Typically, the documents (i.e., document objects) contained within a shared repository are identified using a URL (Uniform Resource Locator). The user interface is thus a series of HTML (HypterText Markup Language) pages or the like. This allows the document repository to be queried using a standard web browser by simply selecting a hyperlink to obtain the desired document.
In contrast, recommender systems provide personalized recommendations that take into account similarities between people based on their user profiles. An example of a recommender system is the Alexa toolbar available on the Internet at www.alexa.com. The toolbar provides a list of recommended web pages worth viewing based on some predetermined filtering criteria. Such a recommender system provides an intelligent agent that provides a way to filter items by personalized measures of quality. Recommender systems learn their users' preferences and recommend items to users by first matching users to each other by way of user profiles.
Another known recommender system, developed by Xerox Corporation, is called Knowledge Pump™. Knowledge Pump provides users with personalized recommendations of documents. When users sign up, they join communities of people with similar interests. Profiler agents track and map each user's interests, learning more about the person each time Knowledge Pump is used. A recommender agent finds matches between new items and user preferences, automatically sending relevant and high quality information to people as it is found. One objective of Knowledge Pump is to help communities, defined by their common interests and practices, to more effectively and more efficiently share knowledge, be it in the form of must-read documents or new ways to work.
A principle element of the Knowledge Pump is the recommendation functionality that is based on community-centered collaborative filtering which filters both by content and by taste (i.e., user preference). Knowledge Pump handles content filtering by relying on user recommendations to classify items into pre-defined communities. Social filtering, matching items to people by first matching people to each other, is accomplished using statistical algorithms and profiles of a collection of users. Further details of Knowledge Pump is disclosed in the article entitled “Making Recommender Systems Work for Organizations” by Natalie S. Glance, Damián Arregui and Manfred Dardenne, Proceedings of PAAM, 1999.
Notwithstanding the existence of both shared document repositories and recommender systems, there continues to exist the need for an improved, integrated system that permits documents forming part of a shared document repository to be simultaneously added and reviewed. Advantageously, retrieval of information in a large shared repository would provide in addition to document metadata but document recommendations from users of the system.